setwd("~/Downloads/Prof Sameer Mathur")
d_dilemma<-read.csv("Data - Deans Dilemma.csv")
placed<-d_dilemma[d_dilemma$Placement_B==1,c(1:23,26)]
sal_genderwise<-aggregate(placed$Salary, list(placed$Gender), mean)
colnames(sal_genderwise)<-c("Gender", "Average salary")
sal_genderwise
## Gender Average salary
## 1 F 253068.0
## 2 M 284241.9
summary(placed$Gender)
## F M
## 97 215
attach(placed)
sal_mean_gender<-aggregate(Salary~Gender, data = placed, FUN = mean)
options(scipen = 999)
boxplot(Salary~Gender, main="Gender-wise salaries", xlab="Gender",ylab="salary",col = c("green","blue"),log = "y")
log.transformed.salary = log(Salary)
t.test(log.transformed.salary~Gender,mean.equal = TRUE)
##
## Welch Two Sample t-test
##
## data: log.transformed.salary by Gender
## t = -2.9732, df = 212.24, p-value = 0.003287
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.1711001 -0.0346748
## sample estimates:
## mean in group F mean in group M
## 12.40435 12.50723
```